New PDF release: Clean Data

By Megan Squire

ISBN-10: 1785284010

ISBN-13: 9781785284014

Save time via gaining knowledge of easy thoughts for cleansing, organizing, and manipulating your data

About This Book

  • Grow your information technological know-how services via filling your toolbox with confirmed innovations for a wide selection of cleansing challenges
  • Familiarize your self with the an important information cleansing methods, and proportion your personal fresh facts units with others
  • Complete real-world initiatives utilizing information from Twitter and Stack Overflow

Who This ebook Is For

If you're a info scientist of any point, newcomers incorporated, and drawn to cleansing up your facts, this can be the e-book for you! adventure with Python or personal home page is thought, yet no past wisdom of information cleansing is needed.

In Detail

Is a lot of it slow spent doing tedious projects corresponding to cleansing soiled info, accounting for misplaced info, and getting ready information for use via others? if that is so, then having the proper instruments makes a severe distinction, and should be an outstanding funding as you develop your facts technology expertise.

The booklet begins by means of highlighting the significance of knowledge cleansing in facts technology, and may assist you to gain rewards from reforming your cleansing strategy. subsequent, you are going to cement your wisdom of the elemental ideas that the remainder of the publication is determined by: dossier codecs, info kinds, and personality encodings. additionally, you will the best way to extract and fresh facts kept in RDBMS, net documents, and PDF files, via sensible examples.

At the tip of the ebook, you can be given an opportunity to take on a number of real-world projects.

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Extra resources for Clean Data

Sample text

We would all be a lot better off if we just got the job done rather than ignoring it, complaining about it, and giving it various demeaning names. Not convinced yet? Consider a different metaphor instead, you are not a data janitor; you are a data chef. Imagine you have been handed a market basket overflowing with the most gorgeous heirloom vegetables you have ever seen, each one handpicked at the peak of freshness and sustainably produced on an organic farm. The tomatoes are perfectly succulent, the lettuce is crisp, and the peppers are bright and firm.

It seems like data is at the center of everything great happening in computing lately. From statisticians to software developers to graphic designers, everyone is suddenly interested in data science. The confluence of cheap hardware, better processing and visualization tools, and massive amounts of freely available data means that we can now discover trends and make predictions more accurately and more easily than ever before. What you might not have heard, though, is that all of these data science hopes and dreams are predicated on the fact that data is messy.

Common formats for text files In this book, we are mostly concerned with text files rather than binary files. ) The three main types of text files we will be concerned with in this book are: The delimited format (structured data)The JSON format (semi-structured data)The HTML format (unstructured data) These files differ in layout (they just look different when we read them), and also in terms of how predictable their structures are. In other words, how much of the file is organized and has structured data?

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Clean Data by Megan Squire

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